This study was aimed at environmentally analyzing an ultrasound-assisted system converting waste cooking oil (WCO) into biodiesel in order to make decisions on its operating conditions. Twenty-seven different experiments (scenarios) carried out at three levels of methanol content, methanolysis temperature, and reaction duration, were compared from environmental viewpoint using the Impact 2002 + life cycle impact assessment approach. The effects of different scenarios on four endpoint impact categories including human health, ecosystem quality, climate change, and resource consumption were quantitatively evaluated and comprehensively discussed. The effects of material and energy flows on the endpoint impact categories were also appraised through a sensitivity analysis. Overall, the experimental variables profoundly affected all the endpoint impact categories considered herein. Methanol content exhibited the highest influence on the studied impact categories, while methanolysis temperature showed the lowest impact on these environmental indices. Overall, methanol:oil molar ratio of 6:1, methanolysis temperature of 60 °C, and reaction duration of 10 min could be recommend as the most suitable operating conditions from both technical and environmental perspectives. The environmental impacts of biodiesel produced at the selected conditions were significantly lower than those of the conventional fossil-based diesel fuel. The sensitivity analysis showed that the electrical power utilized in the process was the most influential impact on the human health and climate change damage categories. The phosphoric acid utilized for neutralizing crude glycerol was the most effective input on the ecosystem quality damage category, while the methanol consumed in the process significantly affected the resource consumption damage category. The outcomes of this study revealed that LCA approach could offer relevant environmental impact indices supporting decision-making on the development of sustainable biodiesel production systems and on the identification of their optimal operating conditions.
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